Services

Fixed scopes, with an edge

AI-assisted data engineering: production-grade pipelines in weeks, not quarters.

Data audit

€1,200–3,000 fixed

1–2 weeks

You know the reporting is messy and you want a written plan before paying for a larger build.

You get

  • A map of the systems that hold the numbers you report
  • Where data quality slips, and where reports disagree
  • The reporting gaps worth closing
  • A written roadmap of what to build and what to leave alone

Pipeline and warehouse

€4,000–12,000 fixed

3–6 weeks

You have two to five sources — project management, a CRM, a shop, ads, or similar — and no single place the numbers come from.

You get

  • Ingestion of those sources into Postgres or BigQuery
  • Models on top of the warehouse
  • One to three dashboards

AI reporting assistant

€3,000–8,000 pilot

2–4 week pilot

You already have a cleaned model, and people want to ask it questions without writing SQL.

You get

  • A text-to-SQL assistant on the model you approve
  • Guardrails so questions stay on that model
  • A pilot with a clear end, rather than an open-ended build

Monthly retainer

€600–2,000 per month

Monthly

A pipeline is already in place and you want it kept up without an open-ended commitment.

You get

  • Monitoring and fixes
  • Small changes inside the cap
  • New reports, as the hours allow
  • An hour cap written into the agreement

Questions that come up

Where should a project start?

With the audit, unless a warehouse and a trusted model are already there. The roadmap from the audit is what a pipeline or an assistant should be priced against.

Why a fixed scope instead of an hourly rate?

The work has a written edge: what is in, how long it runs, and what done means. A retainer adds an hour cap so a month cannot grow on its own.

Is the number on this page the invoice?

No. Each figure is a range to test. The price for a given piece of work is fixed once the scope is agreed, on a call.

Where does the work happen?

Async, from Skopje. Slovenia and the Balkans come first, then remote teams in the EU and the US. We do not need to share an office.

What does the warehouse run on?

Postgres or BigQuery. Models and one to three dashboards are part of the pipeline package. The way data is pulled in depends on the sources, and it is named in the proposal.

Can people ask questions of the data?

That is the assistant pilot: text-to-SQL on a cleaned model, with guardrails. It sits on top of a model you already trust. It is not a way to skip the cleanup.

What happens to client data inside AI tools?